Addressing usage of shared ssd resources in volatile and unpredictable operating environments

ABSTRACT

Systems and methods for optimizing storage system performance are disclosed. A method includes: determining an expected lifetime of each of at least one computing instance; determining a disk data extent evaluation period for each of the at least one computing instance based on the determined expected lifetime; determining an input/output (I/O) wait time threshold for each of the at least one computing instance; determining an I/O wait time of each of the at least one computing instance using the determined disk data extent evaluation period; and in response to the determined I/O wait time of one or more of the at least one computing instance exceeding the determined I/O wait time threshold of the computing instance, moving at least one data extent associated with the one or more computing instance exceeding the determined I/O wait time threshold from hard disk drive storage to solid state drive storage.

BACKGROUND

The present invention generally relates to storage systems and, moreparticularly, to a system and method for optimizing performance ofstorage systems that include solid state drives (SSD) and magnetic harddisk drives (HDD).

Storage systems support SSDs that may provide various benefits overHDDs, such as faster data access and throughput, better performance, andless power consumption. SSDs are capable of reading and writing datamuch more quickly than HDDs. For example, SSDs may be capable of 500 ormore I/O operations per second (IOPS), while HDDs may be capable of only150 IOPS. Accordingly, by moving frequently accessed data extents to SSDstorage, the performance of a storage system may be optimized.

SDDs may be more expensive than HDDs and therefore the total storagevolume in a storage system may be provided by a mix of HDDs and SDDs. Tooptimize the performance of a storage system that includes both HDDs andSSDs, infrequently accessed data extents may be located on HDDs due totheir lower cost and frequently accessed data extents may be located onSSDs due to their higher performance.

Systems may optimize storage system performance by relocating dataextents after an extended evaluation period in order to optimizeperformance. The evaluation period used by optimizers is long andstatic. During this evaluation period, typically between two and 14 dayselapse prior to the optimizer moving data extents between HDDs and SDDs.

SUMMARY

In a first aspect of the invention, there is a method that includes:determining, by a computer device, an expected lifetime of each of atleast one computing instance; determining, by the computer device, adisk data extent evaluation period for each of the at least onecomputing instance based on the determined expected lifetime of thecomputing instance; determining, by the computer device, an input/output(I/O) wait time threshold for each of the at least one computinginstance; determining, by the computer device, an I/O wait time of eachof the at least one computing instance using the determined disk dataextent evaluation period for the computing instance; and in response tothe determined I/O wait time of one or more of the at least onecomputing instance exceeding the determined I/O wait time threshold ofthe computing instance, moving, by the computer device, at least onedata extent associated with the one or more computing instance exceedingthe determined I/O wait time threshold from HDD storage to SSD storage.

In another aspect of the invention, there is a computer program productthat includes a computer readable storage medium having programinstructions embodied therewith. The program instructions are executableby a computing device to cause the computing device to: determine anexpected lifetime of each of at least one data extent associated with atleast one computing instance; determine a disk data extent evaluationperiod for each of the at least one data extent associated with the atleast one computing instance based on the determined expected lifetimeof the data extent; determine an I/O wait time threshold for each of theat least one data extent associated with the at least one computinginstance; determine an I/O wait time of each of the at least one dataextent associated with the at least one computing instance using thedetermined disk data extent evaluation period for the data extent; andin response to the determined I/O wait time of one or more of the atleast one data extent associated with the at least one computinginstance exceeding the determined I/O wait time threshold of the dataextent, move at least one of the one or more of the at least one dataextent associated with the at least one computing instance exceeding thedetermined I/O wait time threshold from HDD storage to SSD storage.

In another aspect of the invention, there is a system that includes: astorage system that includes HDD storage and SSD storage; and acontroller that includes: at least one hardware processor; an expectedlifetime determiner configured to determine an expected lifetime of eachof at least one computing instance, using at least one hardwareprocessor; a disk data extent evaluation period determiner configured todetermine a disk data extent evaluation period for each of the at leastone computing instance based on the expected lifetime of the computinginstance determined by the expected lifetime determiner, using at leastone hardware processor; an input/output (I/O) wait time thresholddeterminer configured to determine an I/O wait time threshold for eachof the at least one computing instance using at least one hardwareprocessor; an I/O wait time determiner configured to determine an I/Owait time of each of the at least one computing instance using the diskdata extent evaluation period for the computing instance determined bythe disk data extent evaluation period determiner, using at least onehardware processor; and a data extent mover configured to, in responseto the I/O wait time of one or more of the at least one computinginstance determined by the I/O wait time determiner exceeding the I/Owait time threshold of the computing instance determined by the I/O waittime threshold determiner, move at least one data extent associated withthe one or more computing instance exceeding the determined I/O waittime threshold from the HDD storage in the storage system to the SSDstorage in the storage system.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is described in the detailed description whichfollows, in reference to the noted plurality of drawings by way ofnon-limiting examples of exemplary embodiments of the present invention.

FIG. 1 depicts a cloud computing node according to an embodiment of thepresent invention.

FIG. 2 depicts a cloud computing environment according to an embodimentof the present invention.

FIG. 3 depicts abstraction model layers according to an embodiment ofthe present invention.

FIG. 4 shows a block diagram of an exemplary system in accordance withaspects of the invention.

FIG. 5 shows a block diagram of an exemplary cloud control programmodule in accordance with aspects of the invention.

FIG. 6 shows a flowchart of a method in accordance with aspects of theinvention.

DETAILED DESCRIPTION

The present invention generally relates to storage systems and, moreparticularly, to a system and method for optimizing performance ofstorage systems that include SSDs and HDDs. Aspects of the invention aredirected to evaluating the relative “hotness” (i.e., access frequency)of data extents using an evaluation period that is dynamicallydetermined based on an expected lifetime of a computing instance. Bydynamically determining the evaluation period, disk resources availableto both short-term transient and long term computing instances may bebalanced. The computing instance may be a cloud computing instance, andthe evaluation may be performed by a cloud controller. Aspects of theinvention may accelerate the movement of data extents from HDD to SSDand back for shorter lived computing instances.

Aspects of the invention may determine the disk data extent evaluationperiod based on the expected lifetime of the cloud computinginstance(s), instead of on a fixed evaluation period. For example, theevaluation period may be determined dynamically based on informationthat a cloud controller has on the current and expected disk workload.Shorter dynamic evaluation periods may be beneficial in environmentssuch as shared cloud environments. These environments may experienceshorter term I/O spikes, as driven by shorter term cloud computinginstance life spans, and accordingly may benefit from the use of SSD.Aspects of the invention may speed up I/O intensive short term workloadsfor cloud products. High priority workloads that run concurrently withother “regular” workloads in a shared storage environment may benefitfrom improved performance.

As described herein, aspects of the invention may include a methodcomprising: determining, by a computer device, an expected lifetime ofeach of at least one computing instance; determining, by the computerdevice, a disk data extent evaluation period for each of the at leastone computing instance based on the determined expected lifetime of thecomputing instance; determining, by the computer device, an I/O waittime threshold for each of the at least one computing instance;determining, by the computer device, an I/O wait time of each of the atleast one computing instance using the determined disk data extentevaluation period for the computing instance; and in response to thedetermined I/O wait time of one or more of the at least one computinginstance exceeding the determined I/O wait time threshold of thecomputing instance, moving, by the computer device, at least one dataextent associated with the one or more computing instance exceeding thedetermined I/O wait time threshold from HDD storage to SSD storage.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as Follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as Follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as Follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 1, a schematic of an example of a cloud computingnode is shown. Cloud computing node 10 is only one example of a suitablecloud computing node and is not intended to suggest any limitation as tothe scope of use or functionality of embodiments of the inventiondescribed herein. Regardless, cloud computing node 10 is capable ofbeing implemented and/or performing any of the functionality set forthhereinabove.

In cloud computing node 10 there is a computer system/server 12, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 12 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, hand-held or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 12 may be described in the general context ofcomputer system executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 1, computer system/server 12 in cloud computing node 10is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 12 may include, but are not limitedto, one or more processors or processing units 16, a system memory 28,and a bus 18 that couples various system components including systemmemory 28 to processor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnects (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a nonremovable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further depicted and described below,memory 28 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 42 generally carry out the functions and/ormethodologies of embodiments of the invention as described herein.

Computer system/server 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing device, a display 24, etc.;one or more devices that enable a user to interact with computersystem/server 12; and/or any devices (e.g., network card, modem, etc.)that enable computer system/server 12 to communicate with one or moreother computing devices. Such communication can occur via Input/Output(I/O) interfaces 22. Still yet, computer system/server 12 cancommunicate with one or more networks such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 20. As depicted, network adapter 20communicates with the other components of computer system/server 12 viabus 18. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 12. Examples, include, but are not limited to: microcode,device drivers, redundant processing units, external disk drive arrays,RAID systems, tape drives, and data archival storage systems, etc.

Referring now to FIG. 2, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 2 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 3, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 2) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 3 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and mobile desktop 96.

Referring back to FIG. 1, the program/utility 40 may include one or moreprogram modules 42 that generally carry out the functions and/ormethodologies of embodiments of the invention as described herein (e.g.,such as the functionality provided by resource provisioning 81).Specifically, the program modules 42 may determine an expected lifetimeof each of at least one computing instance; determine a disk data extentevaluation period for each of the at least one computing instance basedon the determined expected lifetime of the computing instance; determinean I/O wait time threshold for each of the at least one computinginstance; determine an I/O wait time of each of the at least onecomputing instance using the determined disk data extent evaluationperiod for the computing instance; and in response to the determined I/Owait time of one or more of the at least one computing instanceexceeding the determined I/O wait time threshold of the computinginstance, move at least one data extent associated with the one or morecomputing instance exceeding the determined I/O wait time threshold fromHDD storage to SSD storage. Other functionalities of the program modules42 are described further herein such that the program modules 42 are notlimited to the functions described above. Moreover, it is noted thatsome of the modules 42 can be implemented within the infrastructureshown in FIGS. 1-3. For example, the modules 42 may be representative ofa cloud controller 410 as shown in FIGS. 4 and 5.

FIG. 4 shows a block diagram of an exemplary system 400 in accordancewith aspects of the invention. The system 400 includes a cloudcontroller 410 that communicates with a storage system 450 via acomputer network 490. The network 490 may be any suitable network suchas a LAN, WAN, or the Internet. The cloud controller 410 and the storagesystem 450 may be physically collocated, or may be situated in separatephysical locations.

The cloud controller 410 may be situated in the cloud computingenvironment 50 on one or more of the nodes 10 shown in FIG. 2. The cloudcontroller 410 may be implemented as hardware and/or software usingcomponents such as mainframes 61; RISC (Reduced Instruction SetComputer) architecture based servers 62; servers 63; blade servers 64;storage devices 65; networks and networking components 66; virtualservers 71; virtual storage 72; virtual networks 73, including virtualprivate networks; virtual applications and operating systems 74; andvirtual clients 75 shown in FIG. 3.

The storage system 450 may also be situated in the cloud computingenvironment 50 on one or more of the nodes 10 shown in FIG. 2. Thestorage system 450 may be implemented as hardware and/or software usingcomponents such as mainframes 61; RISC (Reduced Instruction SetComputer) architecture based servers 62; servers 63; blade servers 64;storage devices 65; networks and networking components 66; virtualservers 71; virtual storage 72; virtual networks 73, including virtualprivate networks; virtual applications and operating systems 74; andvirtual clients 75 shown in FIG. 3.

According to an embodiment, the cloud controller 410 may include a cloudcontrol program module 420, a master scheduler database 430, and astorage system characteristics database 440.

The cloud control program module 420 according to an embodiment mayinclude hardware and/or software and may be one or more of the programmodules 42 shown in FIG. 1. According to an embodiment, the cloudcontrol program module 420 includes program instructions for executing acloud control program. The program instructions included in the cloudcontrol program module 420 of the cloud controller 410 may be executedby one or more hardware processors. According to an embodiment, thecloud control program performs functions related to optimizing theperformance of storage systems, as discussed below. The cloud controlprogram may also perform other functions, for example, creating anddestroying capacity (i.e., automatically scaling cloud computinginstances or jobs).

According to embodiment, the cloud control program of the cloud controlprogram module 420 may function as follows: (1) each time a job starts,the cloud control program may obtain information about the job from themaster scheduler database 430; (2) the cloud control program may alsoobtain access information for the cloud instance where the job isrunning; (3) the cloud control program may obtain information about allof the “competing” jobs that are either currently running or will startto run before the job completes, including all jobs whose current statusis “running” and all jobs whose current status is “idle” but areestimated to start before the job completes; (4) given all of the aboveinformation that was collected, the cloud control program may thenperiodically monitor the I/O wait time, based on the I/O monitorinterval in the master scheduler database 430, to determine if it hasexceeded a threshold for the job; and (5) based on the job exceeding thethreshold, the job is now eligible to have data extents migrated tofaster storage medium (i.e., SSD or flash).

A policy based approach may be used to determine how to move dataextents for all relevant jobs to the best class of storage medium, sothat I/O wait time is minimized based on real time job priority. Thecloud control program uses these policies to direct the data of higherpriority jobs to faster storage resources.

Still referring to FIG. 4, the master scheduler database 430 accordingto an embodiment may be included within the cloud controller 410 or maybe separate from the cloud controller 410 but in communicationtherewith. The master scheduler database 430 may be implemented as anytype of database. The cloud controller 410 may interact with the masterscheduler database 430 and access data therein using any general-purposedatabase management system or a special-purpose database managementsystem. The cloud controller 410 may interact with the master schedulerdatabase 430 and access data therein using structured query language(SQL), open database connectivity (ODBC), Java database connectivity(JDBC), or any other method. The master scheduler database 430 may be arelational database, an object database, a NoSQL database, a flat filedatabase, an extensible markup language (XML) database, or any otherorganized collection of data.

The master scheduler database 430 according to an embodiment may storeinformation including but not limited to (1) a job name, (2) a jobdescription, (3) a job schedule, (4) a job start time, (5) an estimatedjob duration, (6) an estimated storage amount accessed, (5) a jobpriority, (6) an I/O wait time threshold, (7) an I/O monitor interval,and/or (8) a current job status.

The job name stored in master scheduler database 430 according to anembodiment may be a name for a particular cloud computing instance orjob. In an exemplary scenario where a large retail organization ishaving a one day sale on their public internet site which is hosted in ashared cloud environment, the job name may be a name that identifies thecloud computing instance as being associated with the one day sale.

The job schedule stored in master scheduler database 430 according to anembodiment may include information on particular days of the week whenthe particular cloud computing instance or job will run (e.g.,Monday/Wednesday/Friday) or particular dates when a job will run. Thejob start time may be a time of day when the particular cloud computinginstance or job will start. The estimated job duration may be anestimated length of time the particular cloud computing instance or jobwill run or may be an estimated completion time and date for theparticular cloud computing instance or job.

The estimated storage amount accessed stored in master schedulerdatabase 430 according to an embodiment may include information aboutthe size of various data extents accessed by the particular cloudcomputing instance (e.g., in bytes, kilobytes, megabytes, gigabytes,terabytes, petrabytes, exabytes, or any other unit) or job includinginformation about an amount information read or written from the variousdata extents by the particular cloud computing instance or job.

The job priority stored in master scheduler database 430 according to anembodiment may be a value selected from a set of predefined values andmay indicate a priority level of a particular cloud computing instanceor job. For example, the job priority may 0 to indicate a high priorityjob, 1 to indicate a normal priority job, or 2 to indicate a lowpriority job. Any other set of predefined values may be used instead.Alternatively, the job priority may be an arbitrary value representing arelative priority of a particular cloud computing instance or job inrelation to other cloud computing instances or jobs. For example, a setof cloud computing instances or jobs may be assigned various valuesranging from 0 to 100, with the cloud computing instance or job havingthe assigned priority closest to 0 having the highest priority and thecloud computing instance or job having the assigned priority closest to100 having the lowest priority.

The I/O wait time threshold stored in master scheduler database 430according to an embodiment may be a maximum acceptable percentage oftime that a CPU used by a particular cloud computing instance or job isblocked waiting for synchronous acknowledgement that a disk write wassuccessful. For example, for a particular cloud computing instance orjob, the I/O wait time threshold may be 5%, or it may be 20%.

According to another embodiment, the I/O wait time threshold may be amaximum acceptable length of time that a CPU used by a particular cloudcomputing instance or job is blocked waiting for synchronousacknowledgement that a disk write was successful. According to yetanother embodiment, the I/O wait time threshold may be a maximumpercentage or length of time that a CPU used by a particular cloudcomputing instance or job is I/O bound, or in other words, waiting forI/O operations to be completed. A CPU used by a particular cloudcomputing instance or job may be I/O bound when more time is spentrequesting data than processing data.

The I/O monitor interval stored in master scheduler database 430according to an embodiment may be a static or rolling window over whichaverage I/O wait time for a particular cloud computing instance or jobis measured. According to another embodiment, the I/O monitor intervalmay be an interval at which a point-in-time I/O wait time for aparticular cloud computing instance or job is measured.

The current job status stored in master scheduler database 430 accordingto an embodiment may be information indicating whether a particularcloud computing instance or job is running or not running.

The master scheduler database 430 may store other information instead ofor in addition to the information described above. Additionally, themaster scheduler database 430 may omit various information describedabove.

The storage system characteristics database 440 according to anembodiment may be included within the cloud controller 410 or may beseparate from the cloud controller 410 but in communication therewith.The storage system characteristics database 440 may be implemented asany type of database. The cloud controller 410 may interact with thestorage system characteristics database 440 and access data thereinusing any general-purpose database management system or aspecial-purpose database management system. The cloud controller 410 mayinteract with the storage system characteristics database 440 and accessdata therein using structured query language (SQL), open databaseconnectivity (ODBC), Java database connectivity (JDBC), or any othermethod. The storage system characteristics database 440 may be arelational database, an object database, a NoSQL database, a flat filedatabase, an extensible markup language (XML) database, or any otherorganized collection of data.

The storage system characteristics database 440 according to anembodiment may store information related to the storage system 450,including but not limited to (1) number and type of disk drives, (2)total usable storage by type, (3) redundant array of independent disks(RAID) information, and/or (4) access information for the storage system450.

The information on the number and type of disk drives stored in thestorage system characteristics database 440 according to an embodimentmay include information on a number of HDDs and a number of SSDs in thestorage system 450.

The information on total usable storage by type stored in the storagesystem characteristics database 440 according to an embodiment mayinclude information on the total size of storage (e.g., in bytes,kilobytes, megabytes, gigabytes, terabytes, petrabytes, exabytes, or anyother unit) available across all of the HDDs in the storage system 450as well as information on the total size of storage available across allof the SSDs in the storage system 450.

The RAID information stored in the storage system characteristicsdatabase 440 according to an embodiment may include information as aRAID level of the storage system 450 and stripe size utilized in thestorage system 450.

The access information for the storage system 450 stored in the storagesystem characteristics database 440 according to an embodiment mayinclude information to enable access to real time information regardingthe storage system 450 and/or information to enable requests or commandsto be sent to the storage system 450.

The storage system 450 may be situated in the cloud computingenvironment 50 on one or more of the nodes 10 shown in FIG. 2. Thestorage system 450 may be shared by multiple cloud computing instancesor jobs. In other words, data extents associated with multiple cloudcomputing instances or jobs may be stored in the storage system 450.

The storage system 450 may be implemented as hardware and/or softwareusing components such as mainframes 61; RISC (Reduced Instruction SetComputer) architecture based servers 62; servers 63; blade servers 64;storage devices 65; networks and networking components 66; virtualservers 71; virtual storage 72; virtual networks 73, including virtualprivate networks; virtual applications and operating systems 74; andvirtual clients 75 shown in FIG. 3.

According to an embodiment, the storage system 450 shown in FIG. 4 mayinclude one or more HDDs 460-1, 460-2, . . . , 460-n forming a HDDstorage array 465. The storage system 450 may further include one ormore SSDs 470-1, 470-2, . . . , 470-n forming an SSD storage array 475.The HDDs 460-1, 460-2, . . . , 460-n forming the HDD storage array 465may be physically collocated, or may be situated in separate physicallocations. The SSDs 470-1, 470-2, . . . , 470-n forming the SSD storagearray 475 may be physically collocated, or may be situated in separatephysical locations. Likewise, the HDD storage array 465 and the SSDstorage array 475 may be physically collocated, or may be situated inseparate physical locations.

The storage system 450 may also include a storage controller programmodule 480. The storage controller program module 480 according to anembodiment may include hardware and/or software and may be one or moreof the program modules 42 shown in FIG. 1. The storage controllerprogram module 480 according to an embodiment may include programinstructions for executing a storage controller program. The programinstructions included in the storage controller program module 480 ofthe storage system 450 may be executed by one or more hardwareprocessors. According to an embodiment, the storage controller programperforms functions related to the implementation, maintenance, andadministration of the storage system 450, as discussed below, as well asother functions.

FIG. 5 shows a block diagram of an exemplary cloud control programmodule 420 in the cloud controller 410 in accordance with aspects of theinvention. In embodiments, the cloud control program module 420 includesan expected lifetime determiner 500, a disk data extent evaluationperiod determiner 510, an input/output wait time threshold determiner520, an input/output wait time determiner 530, and a data extent mover540.

The expected lifetime determiner 500 of the cloud control program module420 in the cloud controller 410 according to an embodiment determines anexpected lifetime for each cloud computing instance or job in the cloudcomputing environment 50. Alternatively, the expected lifetimedeterminer 500 may determine an expected lifetime for one or more dataextents stored in the storage system 450 and associated with each cloudcomputing instance or job in the cloud computing environment 50.

For example, according to an embodiment, the expected lifetimedeterminer 500 may retrieve information from the master schedulerdatabase 430, for each cloud computing instance or job, regarding thejob schedule, the job start time, and/or the estimated job duration andmay determine an expected lifetime for each cloud computing instance orjob using the retrieved information. The job schedule, the job starttime, and/or the estimated job duration may be previously provided by orstored in the master scheduler database 430 by another program,controller, or process, or may have been previously provided by orstored in the master scheduler database 430 by an administrator,customer, or other user.

Alternatively, according to another embodiment, the expected lifetimedeterminer 500 may use a predetermined expected lifetime for each cloudcomputing instance or job previously provided by or stored in the masterscheduler database 430 by another program, controller, or process, orpreviously provided by or stored in the master scheduler database 430 byan administrator, customer, or other user.

The disk data extent evaluation period determiner 510 of the cloudcontrol program module 420 in the cloud controller 410 according to anembodiment determines a disk data extent evaluation period for eachcloud computing instance or job in the cloud computing environment 50,or for one or more data extents stored in the storage system 450 andassociated with each cloud computing instance or job in the cloudcomputing environment 50, based on the expected lifetime determined bythe expected lifetime determiner 510.

For example, the disk data extent evaluation period determiner 510according to an embodiment may determine a relatively shorter disk dataextent evaluation period for a cloud computing instance or job having arelatively shorter expected lifetime as determined by the expectedlifetime determiner 510. Likewise, the disk data extent evaluationperiod determiner 510 according to an embodiment may determine arelatively longer disk data extent evaluation period for a cloudcomputing instance or job having a relatively longer expected lifetimeas determined by the expected lifetime determiner 510. According to anembodiment, the disk data extent evaluation period determiner 510 maystore information into the master scheduler database 430, for each cloudcomputing instance or job, regarding the determined disk data extentevaluation period (e.g., as an I/O monitor interval).

By way of a non-limiting example, for a cloud computing instance or jobhaving an expected lifetime of 365 days, the disk data extent evaluationperiod determiner 510 may determine a disk data extent evaluation periodof 14 days, or an evaluation period of two days, or any other period. Onthe other hand, for a cloud computing instance or job having an expectedlifetime of one day, the disk data extent evaluation period determiner510 may determine a disk data extent evaluation period of one hour, orten minutes, or any other number.

Alternatively, according to another embodiment, the disk data extentevaluation period determiner 510 may retrieve information from themaster scheduler database 430 (e.g., information regarding apredetermined I/O monitor interval), for each cloud computing instanceor job, and use the retrieved information to determine the disk dataextent evaluation period. The I/O monitor interval may be previouslyprovided by or stored in the master scheduler database 430 by anotherprogram, controller, or process, or may have been previously provided byor stored in the master scheduler database 430 manually by anadministrator, customer, or other user.

According to yet another embodiment, the disk data extent evaluationperiod determiner 510 may use a predetermined disk data extentevaluation period for each cloud computing instance or job, based on theexpected lifetime of the computing instance.

The input/output wait time threshold determiner 520 of the cloud controlprogram module 420 in the cloud controller 410 according to anembodiment determines an I/O wait time threshold for each cloudcomputing instance or job in the storage system 450. For example, theinput/output wait time threshold determiner 520 may retrieve from themaster scheduler database 430, for each cloud computing instance or job,information regarding the I/O wait time threshold. The informationregarding the I/O wait time threshold may be previously provided by orstored in the master scheduler database 430 by another program,controller, or process, or may have been previously provided by orstored in the master scheduler database 430 by an administrator,customer, or other user.

According to another embodiment, the input/output wait time thresholddeterminer 520 may determine the I/O wait time threshold based uponinformation about a job priority provided by or stored in the masterscheduler database 430 by another program, controller, or process, orpreviously provided by or stored in the master scheduler database 430 byan administrator, customer, or other user. The wait time thresholddeterminer 520 may store information in the master scheduler database430 about the determined I/O wait time threshold.

The input/output wait time determiner 530 of the cloud control programmodule 420 in the cloud controller 410 according to an embodimentdetermines an I/O wait time for each cloud computing instance or job inthe storage system 450 using the disk data extent evaluation period forthe computing instance determined by the disk data extent evaluationperiod determiner 510. The I/O wait time determined by the input/outputwait time determiner 530 may be an average I/O wait time for aparticular cloud computing instance or job as measured over the diskdata extent evaluation period for the computing instance determined bythe disk data extent evaluation period determiner 510. According toanother embodiment, the I/O wait time determined by the input/outputwait time determiner 530 may be a point-in-time I/O wait time for aparticular cloud computing instance or job, as measured at an intervalcorresponding to the disk data extent evaluation period for thecomputing instance determined by the disk data extent evaluation perioddeterminer 510.

The data extent mover 540 of the cloud control program module 420 in thecloud controller 410 according to an embodiment determines whether ornot the I/O wait time as determined by the input/output wait timedeterminer 530 for one or more cloud computing instance or job exceedsthe I/O wait time threshold determined by the input/output wait timethreshold determiner 520. If the data extent mover 540 determines thatthe I/O wait time as determined by the input/output wait time determiner530 exceeds the I/O wait time threshold determined by the input/outputwait time threshold determiner 520, then the data extent mover 540causes one or more data extents to be moved from the HDD storage array465 of the storage system 450 to the SSD storage array 475 of thestorage system 450, if the SSD storage array 475 has sufficient space tostore the one or more data extents. According to an embodiment, in theevent that the SSD storage array 475 of the storage system 450 does nothave sufficient space to store the one or more data extents (e.g., theSSD storage array 475 may be at capacity or nearly at capacity), thedata extent mover 540 may cause one or more data extents that are lessfrequently accessed, as compared to the one or more data extents to bemoved to the SSD storage array 475, to be moved from the SSD storagearray 475 of the storage system 450 to the HDD storage array 465 of thestorage system 450. Provided that sufficient space has been madeavailable by such movement, the data extent mover 540 may then cause theone or more data extents to be moved from the HDD storage array 465 ofthe storage system 450 to the SSD storage array 475 of the storagesystem 450.

According to an embodiment, when, for multiple cloud computing instancesor jobs, the I/O wait time as determined by the input/output wait timedeterminer 530 exceeds the I/O wait time threshold determined by theinput/output wait time threshold determiner 520, the data extent mover540 may receive information about a job priority for each of the cloudcomputing instances or jobs exceeding the determined I/O wait timethreshold. The data extent mover 540 may then use the receivedinformation about the job priority to determine particular cloudcomputing instances or jobs for which to move data extents, if the SSDstorage array 475 of the storage system 450 has space, or if space canbe made available as discussed above. This movement may be performed atvarious times, such as during a period of low usage. The data extentmover 540 may maintain a schedule of times at which data extents may bemoved.

By way of a non-limiting example, if the SSD storage array 475 has spaceavailable for data extents associated with five cloud computinginstances or jobs, the data extent mover 540 may cause data extentsassociated with the five cloud computing instances or jobs having thehighest job priority, as selected from the cloud computing instances orjobs exceeding the determined I/O wait time threshold, to be moved.

According to another embodiment, when, for multiple cloud computinginstances or jobs, the I/O wait time as determined by the input/outputwait time determiner 530 exceeds the I/O wait time threshold determinedby the input/output wait time threshold determiner 520, the data extentmover 540 may receive information about a customer priority for each ofthe cloud computing instances or jobs exceeding the determined I/O waittime threshold. The data extent mover 540 may then use the receivedinformation about the customer priority to determine particular cloudcomputing instances or jobs for which to move data extents, if the SSDstorage array 475 of the storage system 450 has space, or if space canbe made available as discussed above. This movement may be performed atvarious times, such as during a period of low usage. The data extentmover 540 may maintain a schedule of times at which data extents may bemoved.

By way of a non-limiting example, if the SSD storage array 475 has spaceavailable for data extents associated with five cloud computinginstances or jobs, the data extent mover 540 may cause data extentsassociated with the five cloud computing instances or jobs having thehighest customer priority, as selected from the cloud computinginstances or jobs exceeding the determined I/O wait time threshold, tobe moved.

According to yet another embodiment, the data extent mover 540 may useboth received information about job priority and customer priority todetermine particular cloud computing instances or jobs for which to movedata extents, if the SSD storage array 475 of the storage system 450 hasspace, or if space can be made available as discussed above. Thismovement may be performed at various times, such as during a period oflow usage. The data extent mover 540 may maintain a schedule of times atwhich data extents may be moved.

By way of a non-limiting example, if the SSD storage array 475 has spaceavailable for data extents associated with five cloud computinginstances or jobs, the data extent mover 540 may cause data extentsassociated with the five cloud computing instances or jobs having thehighest job priority, as selected from the cloud computing instances orjobs exceeding the determined I/O wait time threshold and associatedwith customers having the highest customer priority, to be moved.

According to yet another embodiment, when, for multiple cloud computinginstances or jobs, the I/O wait time as determined by the input/outputwait time determiner 530 exceeds the I/O wait time threshold determinedby the input/output wait time threshold determiner 520, the data extentmover 540 may receive information about an estimated storage amountaccessed for each of the cloud computing instances or jobs exceeding thedetermined 110 wait time threshold. The data extent mover 540 may thenuse the received information about the estimated storage amount accessedas well as information about the available storage space on the SSDstorage array 475 to determine particular cloud computing instances orjobs for which to move data extents. This movement may be performed atvarious times, such as during a period of low usage. The data extentmover 540 may maintain a schedule of times at which data extents may bemoved.

According to yet another embodiment, when, for multiple cloud computinginstances or jobs, the I/O wait time as determined by the input/outputwait time determiner 530 exceeds the I/O wait time threshold determinedby the input/output wait time threshold determiner 520, the data extentmover 540 may receive information about a data extent movement rate fordata extents accessed by each of the cloud computing instances or jobsexceeding the determined I/O wait time threshold. The data extentmovement rate may indicate a time required to move the data extent fromthe HDD storage array 465 to the SSD storage array 475. The data extentmover 540 may then use the received information about the data extentmovement rate as well as information about the expected lifetime asdetermined by the expected lifetime determiner 500 to determineparticular cloud computing instances or jobs for which to move dataextents. For example, if, based on the data extent movement rate, it isdetermined that a data extent associated with a particular cloudcomputing instance or job cannot be moved prior to the end of theexpected lifetime of the cloud computing instance or job, the dataextent mover 540 may avoid moving the data extent associated with theparticular cloud computing instance or job.

According to an embodiment, the data extent movement rate may bedetermined using information about a current load and/or expected loadof the storage system 450. For example, it may be possible to move dataextents more quickly during low-load times (e.g., overnight) withoutnegatively impacting the performance of the storage system 450. On theother hand, it may be necessary to move data extents more slowly duringhigh-load times in order to avoid negatively impacting the performanceof the storage system 450.

According to an embodiment, the data extent mover 540 may cause one ormore data extents to be moved by sending a request to the storage system450 to move the data extent(s) from the HDD storage array 465 to the SSDstorage array 475. The data extent mover may send this request to thestorage controller 480 of the storage system 450. This request may besent to the storage controller 480 as an application programminginterface (API) call.

The storage controller 480 of the storage system 450 may expose an APIthat provides for various “get” requests and “set” requests. “Get”requests provided for by the API may return information regardingresources available to the storage controller 480 such as informationabout the HDD storage array 465, the SSD storage array 475, or any otherinformation. “Set” requests provided for by the API may be used toeffect movement of specified data extents from the HDD storage array 465to the SSD storage array 475 as well as movement of specified dataextents from the SSD storage array 475 to the HDD storage array 465. TheAPI may provide functionality for specifying what data extents to move,when to move the data extents, and how quickly to move the data extents.

FIG. 6 depicts exemplary methods in accordance with aspects of theinvention. The steps of the method may be performed in the system ofFIGS. 4 and 5 and are described with reference to the elements and stepsdescribed with respect to FIGS. 4 and 5.

At step 600, the system determines an expected lifetime for each cloudcomputing instance or job in the cloud computing environment 50, or forone or more data extents stored in the storage system 450 and associatedwith each cloud computing instance or job in the cloud computingenvironment 50. In embodiments, as described with respect to FIGS. 4 and5, step 600 may be performed by an expected lifetime determiner 500 of acloud control program module 420 running on a cloud controller 410.

At step 610, the system determines a disk data extent evaluation periodfor each cloud computing instance or job in the cloud computingenvironment 50, or for one or more data extents stored in the storagesystem 450 and associated with each cloud computing instance or job inthe cloud computing environment 50. In embodiments, as described withrespect to FIGS. 4 and 5, step 610 may be performed by a disk dataextent evaluation period determiner 510 of a cloud control programmodule 420 running on a cloud controller 410.

At step 620, the system determines an I/O wait time threshold for eachcloud computing instance or job. In embodiments, as described withrespect to FIGS. 4 and 5, step 620 may be performed by an input/outputwait time threshold determiner 520 of a cloud control program module 420running on a cloud controller 410.

At step 630, the system determines an I/O wait time for each cloudcomputing instance or job in the storage system 450. In embodiments, asdescribed with respect to FIGS. 4 and 5, step 630 may be performed by aninput/output wait time determiner 530 of a cloud control program module420 running on a cloud controller 410.

At step 640, the system determines for each cloud computing instance orjob whether or not the I/O wait time determined at step 630 exceeds theI/O wait time threshold determined at step 620. In embodiments, asdescribed with respect to FIGS. 4 and 5, step 640 may be performed by adata extent mover 540 running on a cloud controller 410. If the I/O waittime does not exceed the I/O wait time threshold, the flow returns tostep 600. On the other hand, if the I/O wait time exceeds the I/O waittime threshold, the flow proceeds to step 650.

At step 650, the system moves at least one data extent. In embodiments,as described with respect to FIGS. 4 and 5, step 650 may be performed bya data extent mover 540 of a cloud control program module 420 running ona cloud controller 410. The flow then returns to step 600 and the methodmay be repeated.

In embodiments, a service provider could offer to perform the processesdescribed herein. In this case, the service provider can create,maintain, deploy, support, etc., the computer infrastructure thatperforms the process steps of the invention for one or more customers.These customers may be, for example, any business that uses cloudcomputing technology. In return, the service provider can receivepayment from the customer(s) under a subscription and/or fee agreementand/or the service provider can receive payment from the sale ofadvertising content to one or more third parties.

In still additional embodiments, the invention provides acomputer-implemented method, via a network. In this case, a computerinfrastructure, such as computer system/server 12 (FIG. 1), can beprovided and one or more systems for performing the processes of theinvention can be obtained (e.g., created, purchased, used, modified,etc.) and deployed to the computer infrastructure. To this extent, thedeployment of a system can comprise one or more of: (1) installingprogram code on a computing device, such as computer system/server 12(as shown in FIG. 1), from a computer-readable medium; (2) adding one ormore computing devices to the computer infrastructure; and (3)incorporating and/or modifying one or more existing systems of thecomputer infrastructure to enable the computer infrastructure to performthe processes of the invention.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

What is claimed is:
 1. A method comprising: determining, by a computerdevice, an input/output (I/O) wait time threshold for a computinginstance; determining, by the computer device, an I/O wait time of thecomputing instance; and in response to the determined I/O wait time ofthe computing instance exceeding the determined I/O wait time thresholdof the computing instance, moving, by the computer device, a data extentassociated with the computing instance exceeding the determined I/O waittime threshold from hard disk drive (HDD) storage to solid state drive(SSD) storage.
 2. The method according to claim 1, further comprisingdetermining, by the computer device, a disk data extent evaluationperiod for the computing instance, wherein the I/O wait time of thecomputing instance is determined using the disk data extent evaluationperiod for the computing instance.
 3. The method according to claim 1,further comprising receiving a job priority for the computing instanceexceeding the determined I/O wait time threshold, and wherein the movingthe data extent comprises determining the data extent to be moved usingthe received job priority for the computing instance exceeding thedetermined I/O wait time threshold.
 4. The method according to claim 3,further comprising receiving a customer priority for the computinginstance exceeding the determined I/O wait time threshold, and whereinthe moving the data extent further comprises using the received customerpriority in the determining the data extent to be moved.
 5. The methodaccording to claim 1, further comprising receiving an estimated storageamount accessed for the computing instance exceeding the determined I/Owait time threshold, and wherein the moving the data extent comprisesdetermining the data extent to be moved using the received estimatedstorage amount accessed for the computing instance exceeding thedetermined I/O wait time threshold.
 6. The method according to claim 1,further comprising determining a data extent movement rate for each of aplurality of data extents, the data extent movement rate indicating atime required to move the data extent from HDD storage to SSD storage,and wherein the moving the data extent comprises determining the dataextent to be moved using the determined data extent movement rate and adata extent size for the data extent.
 7. The method according to claim6, wherein the data extent movement rate is determined using informationabout one of a current load and an expected load of the storage system.8. The method according to claim 1, wherein the moving the data extentcomprises a cloud controller sending a request to move the data extentfrom HDD storage to SSD storage to a storage controller.
 9. A computerprogram product comprising a computer readable storage medium havingprogram instructions embodied therewith, the program instructionsexecutable by a computer device to cause the computing device to:determine an input/output (I/O) wait time threshold for each of at leastone data extent associated with at least one computing instance;determine an I/O wait time of each of the at least one data extentassociated with the at least one computing instance; and in response tothe determined I/O wait time of one or more of the at least one dataextent associated with the at least one computing instance exceeding thedetermined I/O wait time threshold of the data extent, move at least oneof the one or more of the at least one data extent associated with theat least one computing instance exceeding the determined I/O wait timethreshold from hard disk drive (HDD) storage to solid state drive (SSD)storage.
 10. The computer program product according to claim 9, theprogram instructions further causing the computing device to receive ajob priority for each of the at least one computing instance, andwherein the moving the at least one of the one or more of the at leastone data extent associated with the at least one computing instanceexceeding the determined I/O wait time threshold comprises determiningthe at least one data extent to be moved using the received job priorityfor each of the at least one computing instance.
 11. The computerprogram product according to claim 9, the program instructions furthercausing the computing device to receive an estimated storage amountaccessed for each of the one or more computing instance exceeding thedetermined I/O wait time threshold, and wherein the moving the at leastone of the one or more of the at least one data extent associated withthe at least one computing instance exceeding the determined I/O waittime threshold comprises determining the at least one data extent to bemoved using the received estimated storage amount accessed for each ofthe one or more computing instance exceeding the determined I/O waittime threshold.
 12. The computer program product according to claim 9,the program instructions further causing the computing device todetermine a data extent movement rate for each of a plurality of dataextents, the data extent movement rate indicating a time required tomove the data extent from HDD storage to SSD storage, and wherein themoving the at least one of the one or more of the at least one dataextent associated with the at least one computing instance exceeding thedetermined I/O wait time threshold comprises determining the at leastone data extent to be moved using the determined data extent movementrate and a data extent size for each of the plurality of data extents.13. The computer program product according to claim 12, wherein the dataextent movement rate is determined using information about one of acurrent load and an expected load of the storage system.
 14. Thecomputer program product according to claim 9, wherein the moving the atleast one data extent comprises a cloud controller sending a request tomove the at least one data extent from HDD storage to SSD storage to astorage controller.
 15. A system comprising: a storage system comprisinghard disk drive (HDD) storage and solid state drive (SSD) storage; and acontroller comprising: at least one hardware processor; an input/output(I/O) wait time threshold determiner configured to determine an I/O waittime threshold for each of at least one computing instance using the atleast one hardware processor; an I/O wait time determiner configured todetermine an I/O wait time of each of the at least one computinginstance using the at least one hardware processor; and a data extentmover configured to, in response to the I/O wait time of one or more ofthe at least one computing instance determined by the I/O wait timedeterminer exceeding the I/O wait time threshold of the computinginstance determined by the I/O wait time threshold determiner, move atleast one data extent associated with the one or more computing instanceexceeding the determined I/O wait time threshold from the HDD storage inthe storage system to the SSD storage in the storage system.
 16. Thesystem according to claim 15, wherein the data extent mover is furtherconfigured to: receive a job priority for each of the one or morecomputing instance exceeding the determined I/O wait time threshold; anddetermine the at least one data extent to be moved using the receivedjob priority for each of the one or more computing instance exceedingthe determined I/O wait time threshold.
 17. The system according toclaim 15, wherein the data extent mover is further configured to:receive an estimated storage amount accessed for each of the one or morecomputing instance exceeding the determined I/O wait time threshold; anddetermine the at least one data extent to be moved using the receivedestimated storage amount accessed for each of the one or more computinginstance exceeding the determined I/O wait time threshold.
 18. Thesystem according to claim 15, wherein the data extent mover is furtherconfigured to: determine a data extent movement rate for each of aplurality of data extents, the data extent movement rate indicating atime required to move the data extent from HDD storage to SSD storage;and determine the at least one data extent to be moved using thedetermined data extent movement rate and a data extent size for each ofthe plurality of data extents.
 19. The system according to claim 18,wherein the data extent mover determines the data extent movement rateusing information about one of a current load and an expected load ofthe storage system.
 20. The system according to claim 15, wherein thestorage system further comprises a storage controller, and wherein thedata extent mover is configured to send a request to the storagecontroller in the storage system to move the at least one data extentfrom the HDD storage in the storage system to the SSD storage in thestorage system.